Electroweak Chiral Lagrangian for a Hypercharge-universal Topcolor Model

Electroweak chiral Lagrangian for a hypercharge-universal topcolor model is investigated. We find that the assignments of universal hypercharge improve the results obtained previously from K.Lane's prototype natural TC2 model by allowing a larger Z' mass resulting in a very small T parameter and the S parameter is still around the order of +1Comment: 12 pages, 7 figure

Dynamical Computation on Coefficients of Electroweak Chiral Lagrangian from One-doublet and Topcolor-assisted Technicolor Models

Based on previous studies deriving the chiral Lagrangian for pseudo scalar mesons from the first principle of QCD, we derive the electroweak chiral Lagrangian and build up a formulation for computing its coefficients from one-doublet technicolor model and a schematic topcolor-assisted technicolor model. We find that the coefficients of the electroweak chiral Lagrangian for the topcolor-assisted technicolor model are divided into three parts: direct TC2 interaction part, TC1 and TC2 induced effective Z' particle contribution part, and ordinary quarks contribution part. The first two parts are computed in this paper and we show that the direct TC2 interaction part is the same as that in the one-doublet technicolor model, while effective Z' contributions are at least proportional to the p^2 order parameter \beta_1 in the electroweak chiral Lagrangian and typical features of topcolor-assisted technicolor model are that it only allows positive T and U parameters and the T parameter varies in the range 0\sim 1/(25\alpha), the upper bound of T parameter will decrease as long as Z' mass become large. The S parameter can be either positive or negative depending on whether the Z' mass is large or small. The Z' mass is also bounded above and the upper bound depend on value of T parameter. We obtain the values for all the coefficients of the electroweak chiral Lagrangian up to order of p^4.Comment: 52 pages, 15 figure

Single chargino production via gluon-gluon fusion in a supersymmetric theory with an explicit R-parity violation

We studied the production of single chargino$\tilde{\chi}_1^{\pm}$ accompanied by $\mu^{\mp}$ lepton via gluon-gluon fusion at the LHC. The numerical analysis of their production rates is carried out in the mSUGRA scenario with some typical parameter sets. The results show that the cross sections of the $\tilde{\chi}_1^{\pm}\mu^{\mp}$ productions via gluon-gluon collision are in the order of $1 \sim 10^{2}$ femto barn quantitatively at the CERN LHC, and can be competitive with production mechanism via quark-antiquark annihilation process.Comment: LaTex file, 18 pages, 4 EPS file

Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction

Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment analysis tools. While Convolutional Neural Networks (CNNs) have established a new state-of-the-art in several vision problems, their application to the task of sentiment analysis is mostly unexplored and there are few studies regarding how to design CNNs for this purpose. In this work, we study the suitability of fine-tuning a CNN for visual sentiment prediction as well as explore performance boosting techniques within this deep learning setting. Finally, we provide a deep-dive analysis into a benchmark, state-of-the-art network architecture to gain insight about how to design patterns for CNNs on the task of visual sentiment prediction.Comment: Preprint of the paper accepted at the 1st Workshop on Affect and Sentiment in Multimedia (ASM), in ACM MultiMedia 2015. Brisbane, Australi

Threshold for the Outbreak of Cascading Failures in Degree-degree Uncorrelated Networks

In complex networks, the failure of one or very few nodes may cause cascading failures. When this dynamical process stops in steady state, the size of the giant component formed by remaining un-failed nodes can be used to measure the severity of cascading failures, which is critically important for estimating the robustness of networks. In this paper, we provide a cascade of overload failure model with local load sharing mechanism, and then explore the threshold of node capacity when the large-scale cascading failures happen and un-failed nodes in steady state cannot connect to each other to form a large connected sub-network. We get the theoretical derivation of this threshold in degree-degree uncorrelated networks, and validate the effectiveness of this method in simulation. This threshold provide us a guidance to improve the network robustness under the premise of limited capacity resource when creating a network and assigning load. Therefore, this threshold is useful and important to analyze the robustness of networks.Comment: 11 pages, 4 figure